Research on the Impact of Artificial Intelligence Technology on Supply Chain Resilience
Journal: Modern Economics & Management Forum DOI: 10.32629/memf.v7i1.4870
Abstract
This study aims to clarify the mechanisms by which artificial intelligence (AI) technology enhances supply chain resilience (SCR) across different disruption stages, addressing the gap in existing research that lacks in-depth exploration of AI-driven dynamic capabilities and stage-specific antecedents. Guided by Dynamic Capability Theory and a four-stage SCR framework (preparedness, response, recovery, learning), the research synthesizes relevant literature to analyze AI’s targeted impacts. The findings indicate that AI boosts risk identification and contingency planning in the preparedness stage, enables rapid adjustments via real-time data processing in the response stage, accelerates recovery through resource integration and network optimization, and facilitates knowledge codification for iterative growth in the learning stage. Theoretically, this study enriches Dynamic Capability Theory by specifying AI-enabled dynamic capabilities; practically, it provides enterprises with guidance to align AI applications with stage-specific SCR needs. Limitations include the absence of empirical validation, and future research should conduct quantitative tests across industries and explore differential effects of AI subtypes.
Keywords
AI, supply chain resilience, dynamic capability theory
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[2] Lerch, C.M. et al. AI-readiness and production resilience: empirical evidence from German manufacturing in times of the Covid-19 pandemic. International Journal of Production Research. 2022; 62(15), 5378–5399.
[3] Modgil, S. et al. AI technologies and their impact on supply chain resilience during COVID-19. International Journal of Physical Distribution & Logistics Management. 2022; 52(2):130-149.
[4] Munir, M., Jajja, M.S.S. and Chatha, K.A. Capabilities for enhancing supply chain resilience and responsiveness in the COVID-19 pandemic: exploring the role of improvisation, anticipation, and data analytics capabilities. International Journal of Operations & Production Management. 2022; 42(10):1576-1604.
[5] Balakrishnan, A.S. and Usha, R. The role of digital technologies in supply chain resilience for emerging markets’ automotive sector. Supply Chain Management: an International Journal. 2021; 26(6):654-671.
[6] Ali, A., Mahfouz, A. and Arisha, A. Analysing supply chain resilience: integrating the constructs in a concept mapping framework via a systematic literature review. Supply Chain Management: An International Journal. 2017; 22(1):16-39.
[7] Belhadi, A. et al. Building supply-chain resilience: an artificial intelligence-based technique and decision-making framework. International Journal of Production Research. 2022; 60(14):4487-4507.
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